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imaging, based on absorption, provides good image contrast between high- and low-density materials, such as bones and soft tissue. However, it cannot distinguish subtle density differences between soft
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive
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of the North Sea. Existing automated detection algorithms will be used to identify seals and porpoises. The results will be used to create seasonal acoustic presence maps, investigate differences in community
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the computational activities in a large closed-loop collaboration that includes computational, biotechnological and automation activities, requiring a solid understanding of the different areas involved in
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data requirements, and lower costs for large-scale modelling tasks. PINNs enhance predictive capabilities and efficiency by combining data-driven methods with physical principles. Unlike traditional
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the timing of irrigation develop detection algorithms to identify signals in cloud and precipitation properties during periods of irrigation activities analyse interactions between irrigation, clouds, and
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. It will use signals from different sources—such as radio signals and internal sensors— to maintain robust and accurate PNT, even when satellite signals are weak or missing. A built-in intelligent
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, result-oriented Excellent analytical skills, analyze data, assess different perspectives and draw well-founded conclusions Strong motivation to contribute to a good working and social environment In
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electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
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. -Machine learning code generation for autonomous translation of payload data semantics. -Dictionary learning and algorithms for translation between major data modeling languages. -Model-based System